Augmented reality represents a new area of technology in which for example additional visual information is simultaneously overlaid onto a current optical perception of the real environment. In such cases a basic distinction is made between the so-called “see-through” technology in which the user looks through a transparent image display into the real environment for example, and the so-called “feed-through” technology, in which the real environment is captured for example by a camera and is mixed before reproduction on a display unit with a computer-generated virtual image.
As a result, a user simultaneously perceives both the real environment and also the virtual image elements generated for example by computer graphics as a combined display (sum image). This mixture of real and virtual image components for augmented reality makes it possible for the user to perform his actions by directly including the overlaid and thus simultaneously perceptible additional information.
So that an augmented reality is also possible in mobile situations position changes of the user (e.g. through turning, change of location, change of body attitude and angle of view) are measured and included in the currently generated image reproduction. This capturing of the changes of position can be executed with a plurality of technologies, such as for example mechanical, magnetic, optical and acoustic sensors through to evaluation of the GPS (Global Positioning System) for capturing a change of position.
Of particular interest for augmented reality systems within mobile terminals are so-called video-based techniques or “tracking methods”. In this case optically perceivable elements of the real environment are used for determining a change of position of the user or of the capturing unit capturing the real environment. Such elements are referred to as a rule as “markers” which are provided and encoded specifically for capturing a position change.
These types of tracking method for evaluation of markers in an augmented reality environment are for example known from literature references S. Malik et al.: “Robust 2D Tracking for Real Time Augmented reality”, Procedures of Vision Interface, 2002 and also J. Rekimoto: “Matrix Real Time Object Identification and Registration Method for Augmented Reality”, Procedures of Vision Interface, July 1998.
Furthermore a method for object detection is described in literature reference A. Ansar, et al.: “Linear Solutions for Visual Augmented Reality Registration”, IEEE Symposium for Augmented Reality 2001”, which provides reduced error susceptibility through the use of predetermined estimation algorithms.
Thus, with conventional augmented reality systems, a very high computing power is required to record the environment visualized by the user together with the tracking data of a marker, in order to incorporate virtual images, if possible in real time, into the environment captured by the capturing unit. Above and beyond this, these demands on computing power are further increased by the information provided by a data processing unit from databases, which are to be incorporated to augment the real environment, and their process visualization by creation of virtual components (e.g. computer graphics, animations, video sequences etc.). Only with the appropriate processing speed is a sum image made up of the real image and computer-generated virtual image components produced for the user in the display unit, which because of the small delay is perceived as augmented reality.
A major reason for the high computing power usually required lay especially in the nature of the method used for determining a position of a marker in an augmented reality system relative to a capturing unit or camera. Previously so-called “trial and error” approximations were executed, in which case a reference image of the marker is used and a transformation is applied to this in order to compare the transformed image with the image actually captured. This process is executed iteratively until such time as a sufficiently good match between transformed image and recorded image is available.
These types of augmented reality systems were as a result restricted only to large computers with almost unlimited resources and especially a very high computing power.